Personalizing Local Search with Twitter

We propose a new ranking model for personalized local search. While local search verticals such as Google Local and Yahoo! Local incorporate physical proximity and public sentiment (reviews and ratings), their rankings reflect minimal personalization. We personalize local search by integrating Twitter social network structure and content analysis. Specifically, we infer sentiment for tweets by the user and those he follows which mention local businesses by name. We also provide a Google Android tailored interface and interaction experience for local search with Twitter integration. Evaluation of search accuracy and quality of user experience via a 25 person user study shows both improved search accuracy and anecdotal evidence of greater user satisfaction.